day2 push

models/index_cosine.faiss

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+version https://git-lfs.github.com/spec/v1
+oid sha256:e6932fe0946d8e0df89abd2f34ee2d76a6c4a3cb14de59afe7b3974401374ac9
+size 11679789

models/index_dot.faiss

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+version https://git-lfs.github.com/spec/v1
+oid sha256:70ea9a98e913f55f9fc700b70fdc7c0ba46fa9fab8e9090940145de0535c6b1b
+size 11679789

models/index_l2.faiss

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2c1a9ac9bf3594a2ce1749e946a4ac4f7947a310f5fe0a06e619ef73ac018872
+size 11679789

pages/search.py

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+import streamlit as st
+from sentence_transformers import SentenceTransformer
+from main import show_serial
+import faiss
+import numpy as np
+
+
+@st.cache_resource
+def load_model():
+    return SentenceTransformer("paraphrase-multilingual-mpnet-base-v2")
+
+
+model = load_model()
+
+indices = {
+    'L2': faiss.read_index("models/index_l2.faiss"),
+    'Dot': faiss.read_index("models/index_dot.faiss"),
+    'Cos': faiss.read_index("models/index_cosine.faiss")
+}
+
+with st.form(key='submit'):
+    cols = st.columns(2)
+    with cols[0]:
+        prompt = st.text_area('Ваш запрос')
+    with cols[1]:
+        amount = st.slider(label='Количество рекомендаций', min_value=1, max_value=10, value=5)
+        metrics = st.radio(label='Метрика', options=('L2', 'Dot', 'Cos'), horizontal=True)
+    submit = st.form_submit_button('Искать', use_container_width=True)
+
+if submit:
+    prompt_embedding = model.encode(prompt).astype('float32')
+    prompt_embedding = prompt_embedding[np.newaxis, :]
+
+    if metrics == 'Cos':
+        prompt_embedding = prompt_embedding / np.linalg.norm(prompt_embedding, axis=1, keepdims=True)
+
+    distances, indices_result = indices[metrics].search(prompt_embedding, amount)
+
+    sorted_indices = indices_result[0].tolist()
+    sorted_distances = distances[0].tolist()
+
+    for idx, score in zip(sorted_indices, sorted_distances):
+        show_serial(idx, (score, metrics))